Welcome to "Python For Data Science"! This course is perfect for anyone looking to dive into data science using Python. Whether you're a complete beginner or someone looking to sharpen your skills, we’ve got you covered. We start with the basics of Python and its role in data science, ensuring you feel confident with the foundational programming concepts.
As you progress, you'll solve real-world classification problems, like predicting income levels based on different attributes. You'll also learn regression analysis to predict continuous values, such as car prices, and get hands-on experience with data cleaning, exploratory data analysis, and building models using techniques like linear regression and random forests. Each step is designed to build your knowledge and confidence in handling data science tasks.
In addition to model building, you’ll master data visualization using tools like Matplotlib and Seaborn, helping you create clear, insightful visualizations of data trends. We also focus on feature engineering, teaching you how to transform raw data into meaningful features to boost model performance. By the end of the course "Python For Data Science," you'll have a strong foundation in data science and the practical skills to solve complex data problems using Python. Join us to take your data science expertise to the next level!
Python For Data Science Table of Contents:
- Welcome and Course Overview - 12:41
- Operators in Python - 14:24
- Variables and Data Types in Python - 21:14
- Section 1 Quiz - 10 questions
- Python Data Sequence - I - 14:30
- Python Data Sequence - II - 11:02
- Python Data Sequence - III - 15:12
- Python Data Sequence - IV - 18:52
- Python for Data Science - NumPy - 26:56
- Quiz for Section: Basics of Python for Data Science - 10 questions
- Reading Data - 13:28
- Pandas Data Frame - I - 25:06
- Pandas Data Frame - II - 12:32
- Pandas Data Frame - III - 11:15
- Control Structures - 16:27
- Exploratory Data Analysis - 21:47
- Visualizations - I - 12:43
- Visualizations - II - 30:57
- Handling Missing Data - 19:35
- Exploratory Data Analysis Quiz - 10 questions
- Classification - I - 19:17
- Classification - II - 30:13
- Classification - III - 27:27
- Regression - I - 17:13
- Regression - II - 21:58
- Regression - III - 51:14
- Regression - IV - 35:18
- Capstone Project Quiz - 10 questions
Who is this course for?
- Beginners in Data Science: Perfect for those with little or no prior experience in data science who want to build a solid foundation in Python and data analysis.
- Aspiring Data Scientists: Ideal for individuals looking to transition into a data science career and need to acquire essential skills in Python programming and data manipulation.
- Students and Academics: University students, researchers, and academics seeking to enhance their data analysis capabilities using Python.
- Professionals looking to Upskill: This course is great for working professionals in fields like finance, marketing, and healthcare who want to use data science to improve their decision-making and career advancement.
- Tech Enthusiasts and Hobbyists: Those passionate about technology and data who want to learn how to analyze and visualize data using Python.
- Business Analysts: Analysts aiming to improve their data handling and analysis skills to provide more insightful business intelligence.
Click on the links below to Download Python For Data Science!
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